The present invention relates in general to focusing systems. More particularly, the present invention relates to acquiring physical characteristics of a human being or animal in good focus. Even more particularly, the present invention relates to acquiring a focused image of an iris for iris recognition.
Video cameras are often used to capture images of moving objects and it is critical, in many applications, to automatically determine when the object is properly focused. The focus information may be used to select a specific video frame to be saved on some analog or digital medium, or processed to extract certain information. The focus information may also be used in a feedback control mechanism to modify the parameters of the optical system and thereby automatically compensate for changes in object position and keep the image in focus.
A challenge in imaging, and particularly iris imaging, is the acquisition of images in good focus. Several known techniques have been used for image focus assessment. In U.S. Pat. No. 4,876,608, entitled xe2x80x9cFocus and Signal to Noise Measurement Routines in Input Scannersxe2x80x9d, issued to Eaton, the focus of an electronic scanner is measured by scanning a test pattern composed of lines, and measuring the total contrast; i.e., intensity range observed across the line pattern. This technique is inconvenient because it requires a special test pattern and only measures one small area of the field of view, that where the test pattern is located. U.S. Pat. No. 5,151,583, entitled xe2x80x9cFocus Adjustment Device Having Restricting Means for Restricting a Selecting Action According to the Degree of Nearness of a Distance Measurementxe2x80x9d, issued to Tokunaga et al., describes the use of a separate distance measurement device to measure the distance to the object, compare it with the distance to the current plane of focus of the optical system, and adjust the focusing optics accordingly. It requires the use of a separate image measurement system which may not operate fast enough to function at video rates, and in any case must be carefully calibrated relative to the optical system to provide accurate focusing. U.S. Pat. No. 5,404,163, entitled xe2x80x9cIn-Focus Detection Method and Method and Apparatus Using the Same for Non Contact Displacement Measurementxe2x80x9d, issued to Kubo, describes an algorithm that uses contrast measurements defined as the sum of the nth power of differences in brightness between adjoining pixels. It assesses only localized areas and does not produce an overall assessment of the entire image, and methods for high speed (video-rate) implementation are not disclosed.
When the imaging target is an iris, for the purpose of real-time personal identification, the focusing requirement is especially challenging because of several factors. One factor is the small diameter of an iris (about 1 centimeter). To acquire iris images at reasonable distances, a long (narrow-angle) lens is required. Since the focus depth-of-field of a classical lens system is proportional to its angle-of-view, an iris target will only be in focus over a narrow range of distances.
Another factor is that the iris is a moving target. Eye movements, head movements, and body motion of the subject are inevitable. To prevent motion blur, the video CCD integration time is preferably reduced or strobed. This reduction in light-gathering power at the imaging device leads to a lower optical F/number, and this further reduces the focus depth-of-field.
Yet another factor is the use of restricted wavelengths of illumination. To minimize unpleasantness of the illumination (or even to acquire images covertly), infrared illumination is desirable. But the elimination of most or even all of the visible band further reduces the light energy available at the imaging device, and so further decreases the optical F/number, which in turn reduces focus depth-of-field as above.
Still another factor is that the CCD camera gain (AGC) cannot be greatly increased to allow for higher F/number imaging and thus greater depth-of-field because then CCD noise is amplified, signal-to-noise ratio is reduced, and the discriminable iris information becomes more deeply buried in CCD noise.
Still further, an eye to be imaged will not be positioned initially at any precisely specified distance (as might be achieved, for example, by use of a chin-rest), because of the intrusiveness and inconvenience of any such positioning device. Therefore, image acquisition typically begins in a state of poor focus.
Ideally, a rapid auto-focus lens should be part of an iris recognition system, but current costs for such are prohibitive for most contemplated applications.
Iris identification systems have been developed that are capable of collecting images of the iris and processing them to produce biometric templates. These templates may be used to identify individual irises with extremely low error rates, on the order of 1 in 106. The systems capture the iris images using stationary optical platforms that are often large, complex, and expensive. Prior art systems are difficult to use without minimal cooperation of the subject being identified. As a result, their usefulness in many applications is limited.
Although the art of human recognition systems is well developed, there remain some problems inherent in this technology, particularly the lack of a portable or handheld device specifically designed to solve the problems inherent in capturing a close-up, high-quality, properly focused image of the iris of the eye. Therefore, a need exists for a recognition system that overcomes the drawbacks of the prior art.
The foregoing disadvantages are overcome by a handheld imaging apparatus which can be used to capture high-quality iris images for identification of a person. The iris imager includes a camera, a cold mirror, a lens, an illuminator, and a focus assessment processor. The imager has sensors and indicators which assist a user in aligning and focusing the device. The imager also automatically captures the image when proper positioning is achieved. The focus assessment processor accesses the image and applies certain measurement routines to assess the focus. The output of the focus assessment processor is used to control an indicator. A template representative of the iris features is extracted and then compared to a database of previously stored templates to identify the person.